1. Field of the Invention
The present invention relates generally to analyzing physiologic data, and more specifically, to non-invasively assessing sleep pathology and physiology from coherence measurements.
2. Related Art
At least five percent of the general population suffers from medically significant sleep disorders, the most common being sleep-disordered breathing (also known as sleep apnea). As a major public health concern, sleep disorders contribute to excessive daytime sleepiness and the associated risks of driving accidents, hypertension, heart attacks, strokes, depression, and attention deficit disorders. The prevalence of sleep disorders is much higher (exceeding thirty percent) in select populations such as, individuals having obesity, congestive heart failure, diabetes, and renal failure.
Conventional diagnostic systems for detecting sleep disorders typically involve complex multiple channel recordings in a sleep laboratory and labor intensive scoring, which collectively lead to substantial expense and patient discomfort. An example of a conventional sleep diagnostic system is a full polysomnograph. Polysomnography is the gold standard for detection and quantification of sleep-disordered breathing, and includes sleep staging, scoring of respiratory abnormality (e.g., apneas, hypopneas, flow-limitation, periodic breathing, and desaturation episodes), and limb movements. Typical markers of sleep disorder severity are the sleep fragmentation index, the apnea-hypopnea index, the respiratory disturbance index, an arousal frequency or index, and the oxygen desaturation index.
One of the many limitations of conventional sleep diagnostic systems is the dependence on tedious manual scoring of “events” based on physiologically arbitrary criteria. Only a moderate correlation can be found between these events and cognitive and cardiovascular outcomes. As such, conventional systems leave a significant amount of unexplained variance in effect, and fail to adequately describe the physiologic impact of sleep disorders. Therefore, a quantitative measure that evaluates the impact of sleep disorders on sleep physiology could be useful in clarifying some of the unexplained variance. A continuous biomarker of physiological state may be particularly useful to follow treatment effects. A continuous biomarker may also be useful to discriminate those in whom the seemingly subtle sleep disorder disease is physiologically disruptive. Such physiologically disruptive settings include primary snoring, which in adults, is associated with excessive sleepiness, and in children, is associated with inattentive and/or hyperactive behaviors.
Presently, rapid and accurate throughput of sleep diagnostics does not exist, despite the development of limited forms of sleep testing that include various combinations of airflow, respiratory effort, electrocardiogram (ECG), and oximetry. This is especially problematic in conditions such as congestive heart failure and chronic renal failure, where severe and complex forms of sleep apnea may adversely affect both mortality and morbidity. Since conventional sleep studies are so expensive, information on sleep effects are typically limited in the pre-approval assessments of drugs used in neurological and psychiatric practice.
Therefore, a need exists to develop a technology that can provide a simple, inexpensive, repeatable measure of the presence and impact of a variety of sleep disruptive stimuli (such as noise, pain, drugs, mood disorders, disordered breathing) on sleep state physiology and stability.